> Ph.D. Thesis Defense
>
>
> Speaker             :  Mr. Swaprava Nath
> Title               :  Mechanism Design for Strategic Crowdsourcing
> Faculty Advisor     :  Prof.  Y. Narahari
>
> Date                :  Tuesday, December 17, 2013
> Time                :  11:30 AM
> Venue               :  CSA Multimedia Class (Room No. 252, First Floor)

>
> Abstract
>
> This thesis looks into the economics of crowdsourcing using
> game theoretic modeling. The art of aggregating information and expertise
> from a diverse population has been in practice since a long time.
>
> The Internet and the revolution in communication and computational
> technologies has made this task easier and given birth to a new era of
> online resource aggregation, which is now popularly referred to as
> crowdsourcing. Two important
> features of crowdsourcing are: (a) crowdsourcing
> is always human driven, hence the participants are rational and intelligent
> and they experience a payoff in some form through their participation, and
> (b) the participants are connected over a social network. To understand
>
> the behavior and the outcome of such a strategic crowd, we need to
> understand the economics of a crowdsourcing network. In the thesis,
> we have considered the following three major facets of the crowdsourcing
> problem.
>
> (i) Elicitation of the true qualities of the crowd workers:
> as the crowd is often unstructured and unknown to the designer, it is
> important to determine if the crowdsourced job is indeed performed at the
> highest quality.
>
> (ii) Resource critical task execution:  due to the diverse geographical,
> cultural, socio-economic reasons, crowdsourcing entails certain
> manipulations that are unusual in the classical theory. The design
> has to
> be robust enough to handle fake identities or information provided
> by the crowd.
>
> (iii) Improving the productivity of the crowdsourcing network: as the
> designer's goal is to maximize some measurable output of the crowdsourcing
>
> system, an interesting question is how one can design the network and/or
> the incentive scheme so that the system performs at the optimal level
> considering the strategic nature of the individuals.
>
> In the thesis, we provide novel solutions to all the questions above
>
> using game theoretic modeling and mechanism design innovations. Our
> investigation helps in understanding certain limits of achievability,
> and provides design protocols in order to make crowdsourcing more
> efficient.
>
>
> ALL ARE WELCOME
>
>